Unlocking Ecommerce Success: How Data Analytics Powers Smart Decision-Making

How do you know if your email or Google Ad campaign is working, and if it is working, is it the best approach?

How would you know if your customers are dropping off your website, how long they stay on, and how many make a buying decision without guessing?

Data analytics can answer these questions.

So, what is data analytics? On a broad level, data analytics is aggregating and interpreting market-level information and behaviors. In Ecommerce businesses, data analytics involves collecting data about customer habits and website performance to maximize sales opportunities. 

Data analytics can be collected in real-time, enabling Marketing and Sales to rapidly adjust campaigns based on website performance, response rates from social media, ad campaigns, and online store activity. Marketing campaigns can be more effective by carefully crafting and adjusting the user experience. 

These are the various methods data analytics can use to improve sales.

Improve the Customer Experience

How are your customers engaging with your online store, and at the very first touch, what are they seeing? 

Data analytics can show that, for example, 60% of your customers view the store via a mobile device. However, you either need to optimize your website or even have a mobile version that reformats itself for your mobile users. You will frustrate the user, resulting in customers dropping off your online store before purchasing.  

Tracking a buyer's behavior can develop a strategy; today's analytic tools enable a view into an individual's online trail, whether they are following a brand, how long they stay on a site, and whether they have purchased similar items historically. With this information, business owners can identify a shopper's likes and dislikes, buying patterns, and seasonal buying patterns and adjust their campaigns, calls to action, and website appearance.

Personalized Shopping Experiences is a Fundamental

In the Ecommerce world, online retailer Amazon is king of personalizing the shopping experience for customers. Personalization is important because a recent study from Elastic shows that 84% of shoppers will purchase more if their experience is personalized with brands and products they like and receive offers on those products.

Retailer Amazon has personalized features based on their data analytics, like: "popular products inspired by this item" and several more recommendation links with product thumbnails. Personal recommendations drive roughly 1/3 of Amazon's total revenue.

Review Mining Minimizes Customer Pain Points

Review mining is a data analytics process that gathers customer opinions on a product. However, understanding what customers like and dislike, a business can promote, demote, or de-list products to maximize sales and streamline inventories.

Review mining aggregators pull data from on-site reviews, 3rd party reviews, social media, forums, and Q&As. Essentially, review mining identifies shoppers' brand and product loyalty. Many shoppers' first choice is on other's reviews. Shoppers are looking for answers on ease of use, durability, quality, and utilization; the goal is to solve shopper's pain points by identifying high-quality and valuable products and services.

With review mining analytics, businesses can develop marketing campaigns surrounding the idea of a product or service that addresses a specific pain point. Companies can improve their product pages by promoting well-reviewed items with confidence. Their customer service adjusted to promote a product as being better than another brand's product because of its highly reviewed qualities.

Quality Customer Service Equals Loyal Customers

Have you ever been on hold by customer service, and it affected your perception of the business? Similarly, have you had an immediate call pickup and a courteous representative who could solve your problem? Customer service is no longer just viewed as a cost center but a revenue center because, if delivered with quality, it is critical to retaining loyal customers.

A study by Harvard Business School indicates that "increasing customer retention rates by 5% increases profits by 25% to 95%." Data analytics can show how many customers are in a queue and how long they stay on hold, and businesses can adjust staffing and training needs to improve their service. In addition, every customer service interaction has an obligatory survey. This data point is equally essential in customer perception and experience, was the representative courteous, attentive, knowledgeable, and resourceful. With these data analytic touchpoints, businesses can improve the retention of their most loyal customers and create new ones.

Loyal customers already love your brand, so why not give them special treatment? Numerous data analytic-driven studies show that most customers offered a loyalty program not only participate but purchase more, stay longer in the online store, and look to maximize their use of the loyalty program.

Optimized Pricing is Dynamic Pricing

To compete in today's Ecommerce industry, the old-fashioned fixed pricing scheme of calculating a profit margin and then affixing it to a site forever until promoted won't drive sales. Developing a dynamic pricing plan requires large data sets from competitor's pricing. Real-time data analytics of pricing can help marketing and sales adjust pricing so it can compete with other online retailers. 

Demand Forecasting Optimizes Inventory Control

Ecommerce businesses face huge decisions on how much inventory to stock. Overstocking means capital is tied up in carry costs and may mean lower profit margins when it comes time to liquidate a particular product through sales or promotions. On the other hand, understocking will decrease customer satisfaction and may result in canceled orders. 

Demand forecasting data analytics can help. By pulling sales histories, buying patterns and seasonal buying patterns emerge. The data also can include:

• Marketing forecasts.
• Sales departments provide future projections.
• Data scientists are projecting future buying trends.

All this data creates accurate forecasts and maximizes inventory manufacturing, procurement, and storage.

The Data Analytics Market for Ecommerce Will Only Grow in Size and Importance

Data Analytics Wrap-Up

There are many approaches and emphasis a business can take with data analytics. The idea is that companies must know their customers, their likes, their pain, their experiences, their loyalty, and their trends. A business needs to know these data sets and how to address them to ensure a business's bottom line can succeed. If you can't measure your customer's wants and behaviors, you can't improve them.