Today, more and more businesses are embracing the concept of big data rather than treating it like just another buzz-phrase. This new trend is a blessing to e-commerce owners looking to make the most of what the Internet can offer: data analytics in spades and metrics in massive quantities.
E-commerce aficionados are commending the use of data in crafting e-commerce strategies because it provides access to new approaches to online sales. Successful online businesses are developing robust digital commerce solutions with the aid of data to make better marketing decisions that identify and resolve the customer issues. As online retailers are gathering and analyzing data at volumes, new forms of personalization, custom pricing, and customer service are attainable at previously unknown velocities.
The Challenges for Online Retailers
More than one third of online retailers aren’t aware of their available data and most of them admit that the silos are the primary hurdle for using such information.
- 51% – Unable to access data, which creates an obstacle to measuring marketing ROI.
- 42% – Do not have the resources or technology to link individual customer data together.
- 39% – Rarely collect and store data.
- 45% – Do not use data effectively to personalize marketing communications.
- 29% – Have small amount of customer data.
So, what’s the catalyst for such rapid adoption of data analytics in the eCommerce space?
1. Personalization
The eCommerce behemoths like Amazon have already mastered personalized stores for many years. With fast web server technologies and big data, online businesses can enhance the websites which are filled with relevant products based on the history and real-time behavior of a customer and their personal preferences. Automated recommendations have a significant impact on conversions and offer lucrative rewards in sales through orders influenced by auto recommendations and personalized eCommerce experiences. Cart abandonment is a widely discussed pain point for eCommerce; retailers can use big data to offer personalized expertise, prevent the potential abandonment and generate more sales.
2. Custom Pricing
Pricing becomes a key differentiator for the customer to buy a product or service from a particular company. To know the best price of the product in the market, a price comparison needs to be done with the existing competitors. This data is scrapped from competitor websites and is used to benchmark against competition thereby providing intelligence to offer discounts on the products or services to be the first choice for the consumer.
3. Product Analysis
For companies that develop and create products based on new trends, data analytics allows you to explore the latest trends through the data collected from search engines, social media, surveys, forums and other online networks; you can learn more out what your customers might want. By filtering the data by characteristics of the customer, you can find out what your target market is interested in, and discover what kinds of new products they may enjoy.
4. Customer Segmentation Analysis
Companies engaging in customer segmentation methodology assume that every customer is unique and that their marketing efforts would be better served if they are target-specific. The process of customer segmentation relies on identifying key differentiators which break customers into groups who can then be targeted with specific deals and discounts. Demographic information such as a customers’ age, race, religion, gender, family size, ethnicity, income, education level, geography and their shopping behavior is taken into account when determining customer segmentation practices.
5. Online Marketing Analytics
Although big data has uncovered new opportunities for businesses to reel in revenue, it’s also created a slew of challenges for marketers. As E-Commerce provides you a virtual environment to buy stuff, they have to market in the virtual environment extensively. The online marketing team works on bidding for ads on Google or other websites. They analyze the funnel of new prospect customers and maximize the likelihood of a customer clicking those ads. They also test what type of layout is better for what type of customers. Retailers also benefit from operational systems, such as an integrated marketing application, that can quickly operationalize new insights and enable marketing teams to move from managing campaigns to managing customer interactions across the brand.
Let’s wrap it up,
Data analytics helps organizations to harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers.
According to a report by Statista, the Big Data market size revenue will increase from 23.7 Billion Dollars (US) in 2016 to 92.2 Billion Dollars (US) by 2026.
Feeling more confident now? Hopefully, these five key trends will help you not just wrap your head around where e-commerce is headed in 2018, but give you lift-off to reach your targets and grow your e-commerce business.
Our eCommerce consulting services can help your brick-and-mortar customers make the transition to e-commerce by offering them a more immersive shopping experience online. How do you see Data analytics transforming the e-commerce industry? Share your thoughts in the comments section.
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Minal Joshi is a content marketer at Krish with a flair for eCommerce and Digital Commerce aspects. She is a MarTech fanatic with a knack of writing with which, she helps brands to curate, create, & commence digital brand positioning. Sharing insights via articles, case studies, eBooks, Infographics, and other forms of content creation is what she lives for. Being an ardent traveler, when not writing, you'll find her sipping coffee into the mountains or petting a stray.
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