Ecommerce has been on the rise over the past couple of years. Global total retail sales are expected to be around $22-trillion, 6% higher than last year. And although growth rates are becoming calmer, sales by the year 2020 is expected to reach $27-trillion. Truly, the future is still bright for ecommerce.
However, what is keeping the industry from achieving even bigger heights is how a vast majority of ecommerce businesses are focusing only on key performance indicators getting only statistics on how theyve performed over a period of time. These are just numbers and do not exactly seek actionable rights.
So what really has to change so that the ecommerce industry will perform better than expected? What can make ecommerce businesses pick up the pace?
Soon to be Old-school Practices
There are some practices that players in the ecommerce industry have been doing, but they shouldnt. Some things that worked before just dont work anymore. Some people just dont fix things until theyre broken, even habits, practices, and processes.
Online businesses get data from their database of orders, products, baskets, visits, users, marketing campaigns, referring links, keywords, and catalog browsing. Some businesses also tap social data from Facebook, Twitter, and Google. Google Analytics is also used. All of these just give you numbers, flow charts, and tables of data that you still need to interpret and properly sort.
After getting the date from these sources, you will then try to analyze them in hopes of getting strong conclusions. But analytics can only answer so much. Analytics can only give you an idea of the following:
- What are the best-selling products per category?
- What is the most viewed product?
- How often does a group of users return to your site?
- What products are most bought by users who already bought something on the same category?
There are some other questions that analytics can answer but answering these questions do not help in getting bigger profits. It is then almost useless to get the answers to such questions. Analytics can give you quantitative data, and you have to analyze deeper to determine qualitative data. It gives you direct answers on what weve talked about above, but can we forecast data with assurance based on its trends? Google Analytics is prone to human error, with people confused with filters vs. segments, enabling demographics, or incorrect implementations of the tracking code resulting to erroneous data.
We cant always go on hunches alone, and we definitely cant rely on improbable data.
Out with the old, In with the new
Data that are obtained and used to satisfy key performance indicators are truly inadequate to help an ecommerce business from knowing what to do in order to get bigger profits. There is a bigger and more complex data that can do otherwise big data.
Big data is the large set of data that describes the day-to-day activity of a business. It is a pool of data so complex that traditional data processing tools, systems, and techniques just wont do. Being able to tap big data will help a business make better decisions, and would definitely lead to bigger profit.
There is also a subset of big data called actionable data. Actionable data is that which after being analyzed, can lead into actions. Actionable data is also that part of the big data that are essential, and should be isolated from mere noise. Actionable data goes beyond just telling you which items have the best ratings, or most visits, and gives you insight on things that truly matter.
With actionable data you would be able to get the following:
- Finding the correlation between elements on your ecommerce site, or a keyword and the chosen link.
- Recommended products and how to offer them
- Trends, or the lack of it
- A products future popularity
- The effect of marketing activities on the sales of product
With the help of actionable data, you can go beyond knowing what products have the most likes and into knowing which products users who buy products after liking them. You will also know what percent of your shoppers are affected by recommendations, giving you the information on what to recommend to a specific group of customers.
To further know what actions to take, Smart Prediction can help. Smart Prediction through artificial intelligence can help you get an idea on what products your customers would buy, by analyzing big data. Smart prediction can help you go beyond knowing what products are bought by customers who have already bought a product, and into how you can make a customer buy a certain product by being able to come up with a message that matches his behavior.
READ: How Predictive Analytics Reinvents These Six Industries
Smart Predictions can help you personalize your ads in order to be more effective. With Smart Predictions, you will know what action to take, and how to do it correctly.
Large Companies are now using Smart Predictions
As smart predictions would need intelligent systems that can process highly complex data, large ecommerce businesses are the first to be able to tap it.
Some of the top companies that have tapped smart predictions are the following:
- Amazon
Through smart predictions, Amazon is able to personalize interaction, capitalize on value over price, predict trends, and improve customer experience. Smart predictions help Amazon make the right decisions, and the results show that smart predictions really help.
- Macys
Macys is able to optimize their product range to the different market segments by analyzing big data. They do this by analyzing out-of-stock rates, sell-through rates, and price promotions. Taking this against data from stock keeping unit, Macys is able to offer customer-centric product ranges.
- eBay
eBay is able to personalize and engage customer experience for all thanks to smart prediction. Being able to handle all the data that eBay generates daily is already overwhelming, but being able to analyze them to make actions that can further increase sales, now thats really something!
- Walmart
Walmart is able to provide personalized insights to users by analyzing social media apps. By understanding the behavior of users on Facebook and Twitter, they are able to provide personalized offers for all types of customers.
- Nordstrom
Nordstrom is able to improve customer service and personalize its ads by understanding customer behavior. Using Wi-Fi signals, Nordstrom was able to obtain valuable insights, something traditional data processing systems just cannot imagine.
2017 is the year you tap Smart Predictions
Smart Predictions are helping big companies become bigger. Its about time that you tap into this amazing piece of technology to help your ecommerce business too! Smart predictions can set you apart from businesses that will stay where they are. Several industries in ecommerce have seen the benefits of big data to further pinpoint their consumers and predict the way they think in completing a purchase. Those in the computer and electronics, online clothing business, automotive, and online retailers are at the forefront of them all.
For ecommerce websites, popular CMS WordPress, Joomla, and Drupal are handling tons of data as customers continue to shop online. Several ecommerce platforms like Woocommerce and Shopify also recognize the increase in demand for big data. Consequently, they are working to provide business intelligence ready for their clients to digest readily, without all the technical mumbo-jumbo.
To really grow, you have to get the full picture, and you have to dig deeper. Smart Predictions can help you with that. In 2017, make it your goal to tap into smart predictions, and from them, you can predict a brighter future for you ecommerce business!
