Data is everywhere, and its structure, recency and relevance all fuel decision making. Data analytics comprises key data on an eCommerce business’s present and foreseeable health and performance. These analytics help you gain a better understanding of your business. The right data forms critical decisions and unearths measures to optimize the supply chain, from the time you receive orders to when they reach your customers’ doorstep.
India’s e-commerce market will reportedly reach US$ 111 billion in two years and US$ 200 billion by 2026. These numbers indicate that identifying and setting key metrics can enable an eCommerce distributor to maintain accountability in terms of the chain of custody, grow their gains, keep their inventory lean and increase customer satisfaction.
Let’s go into why eCommerce analytics are non-negotiable and where to go to find them on an automated smart eCommerce solution!
What are eCommerce Analytics?
Ecommerce analytics contain a range of metrics to let an eCommerce seller keep track of their orders, buyers, preferences and performance. These metrics highlight channel transactions, order volume, shipment statuses and compare them to online trends to enable you to comprehend shifts in buyer behavior. Ultimately you can forecast your sales margin by product performance and keep your inventory lean to combat inventory seasonality.
The primary reason brands need eCommerce analytics is to stay forewarned and mitigate risks. Utilizing this data keeps the competition in check by meeting demand with adequate and quality-compliant stock. With a holistic view of all BAU activities, you can keep an eye and even chalk out a plan to expand your business strategically.
Types of data analysis
There are 4 ways to make sense of data after it is formatted into a report, which are
- Descriptive Analysis
Descriptive analysis is the building block of business intelligence dashboards. It answers the question of what, when and where an event happened. The eCommerce applications include marking key performance indicators (KPIs), monthly revenue and sales reports.
- Diagnostic Analysis
Diagnostic analysis establishes connections between consumer behavior and data and is applied when investigating causes behind dips in revenue. For example, if there’s a server failure or overload on seasonal sales days, there’s an explanation for the surge in failed transactions and escalations.
- Predictive and
Predictive analysis looks at the future and forecasts interdependencies and trends. It reveals previous experiences and can be used to assess risk levels and likelihood of cart conversions.
Prescriptive analysis is the marriage of big data and AI to predict the best course of action in unusual circumstances. It provides all possible outcomes for you to pick the best option of them all. Prescriptive analysis has uses in optimizing product lines, order fulfillment and customer experience. Take inventory expiry reports, for example. This report lets you set a product item’s expiration date so that it gets delisted automatically as the date looms near, ensuring that the only course of action available is to list updated quality across all channels. It optimizes the product line by queuing them on their shelf life so that your inventory comprises only the latest and best performing items.
4 Advantages to Leveraging Data analytics in your eCommerce Business
Customer behavior insights
Data analytics from reports such as SKU performance can help you identify those products that are high and low-selling. Via EasyEcom, this report displays product items by their invoice date and time duration to let you track individual performance and determine if the quantity of returns exceed the expected rate.
In such cases, the seller can preempt and revamp their inventory by incorporating better strategies. Data analytics reveal other key data too, including customer interactions, discovery date and source, preferences and browsing history. This lets brands reposition their stock such that wishlisted items are presented with attractive discounts and favorable return and refund policies that encourage the buyer to proceed with the purchase. eCommerce can even tell you when demand peaks in order to better plan the sales pipeline.
2. Cost Reduction
eCommerce analytics help businesses bring down their costs by pointing out dead stock, damaged and slow-moving inventory. Sellers can accordingly decide to scrap irreparable goods and restore reparable products after they pass quality compliance checks. Analytics can also give you pricing for logistics aggregators to indicate those routes and providers that fulfill orders within the least time and expenses, ensuring you’re conserving your revenue for fruitful endeavors.
3. Better inventory management
Customers shop online due to its convenience, time savings, affordability and more browsing options. But what if your inventory is insufficient at a particular pincode? Or is it in excess and taking up space, leading to increased storage costs? A clear view of supply and demand can not only optimize your warehouses but can ready you for inventory seasonality by forecasting future sales.Pre-SaaS eCommerce, it was difficult to predict expiry and offload items quicker or remove stock. But with measured data, you can price items correctly and update availability by sales channel. For example, if you sell on eBay and Amazon besides your own website, you can modify and adjust the availability to ensure best-selling channels have maximum stock availability around the holidays or events. It also lets you time product launches for when their demand will go up, ensuring your inventory isn’t moving either too quickly or slowly. In other words, you can build your market around evolving demands!
4. Customer loyalty
Loyal clients are the result of a deliberate data analytics strategy. By deliberate, we mean one that gives you relevant data to work with to help you know your customers better. This is what ultimately enables eCommerce businesses to cater to needs and adapt. The company and brand will understand where painpoints originate and what can be done to resolve for them. Take shopping cart abandonment for instance, which currently averages at ~70%. Many buyers are discouraged to proceed further when they face a poor checkout experience. eCommerce sellers can leverage analytics to understand why carts are abandoned and prevent losses upwards of nearly ~USD 2 billion!
The Best Practices to leverage Marketing data in eCommerce Analytics
Now that you know the benefits of having data on your side, here are some practices to make the most of eCommerce analytics
- Consolidate your marketing data across all platforms and sales channels to organize it better. You’ll find this information through your store, mailer lists, CRM platforms and Google Analytics dashboard. A data connector can extract this data from all sources and export it onto an Excel file.
- A purpose-driven data analytics collection strategy can connect the dots between customers and sales figures. Having your data in a single dashboard can establish a clear picture of your business to fix process and operational inefficiencies
- Adjust your data for events, trends and seasonality to seasonality and other trends. This way, you’re playing the long game with SEO and are prepared for the future while meeting current demands.
- Improve site usability and user experience after analyzing user behavior flow. This can also let you find an exact point in the checkout journey where the customer dropped off and what caused it. A reduction in flow could indicate problems in the checkout process which would have resulted in higher cart abandonment rates. Continuous monitoring of this flow is therefore critical.
- Keep tracking the performance of individual items under different product categories to know what are your revenue drivers. Sales reports can tell you the maximum number of a certain product that was sold, which products are making you money and when seasonal purchases are most in demand, which reveals where your customers’ interests lie. You can even push slow-moving inventory by providing related products to the ones already bought, nudging the customer to consider these for their next transaction!
To Wrap Things Up..
eCommerce analytics lets you make choices smartly to drive your company’s growth and improve the bottomline. Once extracted and formatted, data analytics makes your business activities easier to track, and by virtue of association, quicker to improve. Analytics not only point out where your business is doing well, but also lets you know what measures to take to guarantee future success as well, enabling you to evolve, adapt and compete!