The evolution of the internet has paved the way for newer and nimbler business models. With the whole world online today, e-shops are growing at an exponential rate. As you read these lines, millions of people are busy buying from eCommerce platforms. By the year 2040, it is estimated that 95% of all purchases will be through eCommerce.1
As new means make it simpler to open an e-shop, the market has grown exceedingly complex with sporadic competition and disappearing customer loyalty. However, eCommerce businesses have a big advantage over traditional ones. They can quickly adapt to constantly changing customer needs and tap insights on customer behavior and feedback with data. Data empowers eCommerce businesses and sets them apart from the traditional businesses. The digital world allows easy capture of millions of data points on a daily basis, thus making data an indispensable and integral component in eCommerce operations.
Unfortunately, raw data isn’t valuable in itself. It needs to be cleaned and structured to power the decision-making processes. For eCommerce companies with a large pool of data, the secret to being effective is the ability to collect, organize and draw insights from the data in a timely manner.
How can eCommerce businesses leverage data to achieve success?
Pricing is the No. 1 chief driver in an online purchase decision. E-shoppers are always comparing prices online to get the best deal for a preferred product. However, lower prices mean lower margins which affect the eCommerce business profitability. Hence it is crucial to have a rules-based dynamic pricing strategy at all times. If you are always aiming to offer the lowest price in the market, you will have to also prepare yourself to hit volumes to be profitable. Only a data-driven approach can help you price right, and at the same time give you the ability to adapt to market changes and promptly change your price.
For the online shopper, the comparison does not end at pricing. Up to 82% of online shopping carts are abandoned before checkout—the biggest reason being additional costs like shipping, taxes, additional fees, and delivery timelines. Data analytics has now made it possible for e-tailers to gain insights at basket level, thereby keeping a closer tab on competition.
For gaining success on your eCommerce platform, it is imperative to not lose a customer segment to gaps in your catalog. Data on peer products and brands in the market aids decision-making on the optimal assortment mix on the online catalog, and this can be broken down by category, sub-category, even to the attribute level.
However, just the right product mix is not enough for the e-tailer. They need to ensure that the product page has the optimal description and keywords. Below are screenshots of the same product model on two large e-tailer websites. Let’s compare the two descriptions:
Fine-tuning the component elements of a product page can go a long way in optimizing returns on your ecommerce page.
Website 1: Product Details for Brand-Model X
Website 2: Product Details for Brand-Model X
eCommerce outlets are struggling to win the buyer by extending deals and other incentives. In this competitive price war, e-tailers can use the power of data analytics to measure the effectiveness of their promotional campaigns and achieve a higher ROI by setting optimal promotions. Moreover, real-time analytics empowers e-tailers to monitor whether eCommerce businesses are complying with their promotions or not.
Today, data has made it possible for e-tailers to track the voice of customers not only on their website but also on their competitors’ websites. We all know the importance of customer reviews and ratings in a purchase decision and their contribution to an overall brand hygiene score that indicates the brand perception on online marketplaces. Whether competing with big brand products on multi-brand websites or comparing one private label to another that sells a similar product mix, brand hygiene benchmarking is of utmost importance to an e-tailer.
Listening to your customer will also help you serve them better with stronger customer support. Machine learning algorithms simplify customer feedback and help businesses improve their product and customer retention rate.
Besides focusing on the current business scenario, it is also essential to envision and prepare for the future. Data on historical sales can help e-tailers predict future sales. This, in turn, empowers them to have a strong inventory plan and prepare for marketing campaigns ahead of time. Along with this, keeping a tab on current trends on other e-tailer websites can help them react promptly to opportunities to make more sales.
Data is paramount for scale in retail eCommerce. Data drives a strategic business. It enables you to make decisions based on insights – an insight that is only available from large amounts of customer data. Having the right data collection and processing platforms allows for quick analysis and results as well as easy scalability. Data platforms should enable you to continually capture data not just from your own channels, but also from your existing customers’ digital footprints outside your channel. After all, numbers do not lie!
Course5 Intelligence enables brands to thrive in the ecommerce space using real-time competitive insights from websites and online marketplaces.
Our AI-driven competitive intelligence platform, Course5 Compete, provides actionable and data-driven insights on product, price, placement, promotions and people. Learn more about Course5 Compete.
Write to us at email@example.com or speak to our experts to find out how we drive strategy and tactics that will build continued competitive edge for your business.
1. Top 40+ eCommerce Statistics of 2020
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