5 Ways to Use Data to Future-Proof Your E-Commerce Store

Data is the oxygen of every business. The data synthesized from interactions with your customers and visitors can help you grow your business, better understand your customers, and improve your business operations that brings better customer experiences. For e-commerce stores, you can use data to boost sales and analyse patterns in consumer buying behaviour.

As global e-commerce sales continue to grow, the most successful brands will be those that can use data and AI to not only improve customer experiences but also adapt to an ever-changing marketplace. Machine learning can analyse much data across multiple channels to uncover hidden trends, needs and sales opportunities.

Continue reading to understand how data may be utilised in new ways, from customer self-service chatbots to agent assistants that give real-time insights and prompts during customer conversations. The key to the next big thing in CX for e-commerce shops may lay in leveraging data in several innovative ways!

Why should you care about data?
‍

57% of digital marketers use big data analytics to get a high conversion rate in sales.

It would be an understatement to say that COVID-19 had a global impact. Aside from the devastating emotional toll, it has permanently altered the way we do business. Lockdowns and social distancing drove companies over the technological tipping point, requiring them to figure out how to run their operations with a lot less.

Some began mining their untapped treasure mine of data, often known as dark data, to uncover nuggets of insight that may help them make better decisions. Each customer-employee interaction contains valuable information such as your customers' preferences, your team's knowledge and skills, and business workflows.

In addition to providing much needed business intelligence and real-time analytics during uncertain times, dark data can also feed advanced machine learning models. Artificial intelligence can help support end-to-end automation initiatives, which can boost productivity, reduce operating costs, and improve business performance.

Now that you understand the importance of using big data, here are five tips to get you started!

1. Have a data strategy plan in place

Data strategy is a long-term plan for how you will use data to improve your e-commerce business. It is not just about collecting as much information as possible but also making sure that the data collected is used in the right way. At the end of the day, it is about how you plan to manage your company's information assets.

A good data strategy should start from the top down, beginning with the leader or owner and working its way down through teams such as marketing and support to ensure that everyone understands their role in its use. If a borderless e-commerce strategy is being pursued, for example, multilingual data must also be gathered.

Finding ways to use your data is key, as it helps you learn what your customers want and how they behave, which in turn allows you to create products or services that align with those needs. This will allow you to capitalise on emerging shopping trends before they become mainstream, ultimately helping grow your online business.

2. Give your employees the right tools

If data is an information asset, then employees need the right tools to quickly access data and make sense of it. It should ideally be consolidated in one place so that people need not switch between different apps to piece together data, and employees must place trust in the data being accurate and true to use it.

Dark data that was previously overlooked, such as web browsing history and language, should be easily extracted and put to good use. Such information is difficult to get and is not in a human-readable form. Displaying it before a customer interaction, for example, provides your agents with helpful insights about incoming enquiries.

Anticipating the context of enquiries can help agents create better and more relevant customer experiences. When an agent sees that a visitor last visited the pages for promotions and coupons on your website, for example, your agent can quickly refresh themselves on any ongoing marketing campaigns or valid discount coupons.

3. Populate your data engine now

As an e-commerce store owner, you don't have time to build a data engine from scratch. This is a database system that is used to collect and store information about your customers, prospects and employees in one place. Ideally, the same platform you are using for customer and employee interactions should also store all the data.

Without historical data to analyse, machine learning cannot be trained to predict future outputs or to find hidden patterns in unstructured data. Thus, it is important that you start to gather data now for your AI initiatives—the more volume and reliable data you have, the greater the quality of predictions and inferences you will get.

For example, a total experience platform like CINNOX can integrate with your technology stack. Using no-code tools like Zapier or the open API, you can share data from email marketing software like Mailchimp or HubSpot, giving your agents even more insights into how engaged customers or prospects are with your emails.

A prospect who opens and reads every email and clicks on CTAs to view promotional links is more likely to convert with a little more effort. In contrast, a cold lead who has not opened any emails would almost certainly need proactive outreach attempts to learn their shopping objectives or what they will be searching for.

4. Make sure you are using all your data

Data is not just about customer data. When it comes to using data, you can also have a positive impact on your employee experience and prevent agent burnout through the use of interaction analytics. The customer experience can also be improved by optimising the way your agents handle enquiries and deliver outcomes.

By taking advantage of both customer and employee interaction data, you can spot areas for improvement or make tweaks to your workflows for better experiences. When your agents are happy and motivated, they will be inspired to delight customers who will then attract others by word of mouth or sharing of experiences.

One way to leverage employee data is to consolidate historical data from live chat conversations rated 5 stars by customers. When you summarise the context of the interactions, the agent's responses and the reasons for the rating, you can develop better employee training programs and improve agent satisfaction at the same time.

5. Build your business neural network

So, what exactly is a business neural network? If you haven't heard of it yet, this trending buzzword describes a company's approach to doing business by emulating the way the human brain works—algorithms powered by artificial intelligence and machine learning identify underlying relationships hidden within massive datasets.

Like a human nervous system, data flows like signals across different networks, systems and people to record activities and send the appropriate responses. Platforms like CINNOX operate like the brain that houses these neural networks, storing data in a central location from which nuggets of information can be extracted.

Artificial intelligence, however, requires vast amounts of data to train its advanced machine learning models. The more data there is, the more accurate the analysis and results! This data is provided by day-to-day communications, which includes all the information, processes and teams involved in resolving customer enquiries.

One benefit is that the customer journey can be automated from start to finish. Previously, documentation would be used to move the order along the buying journey. For example, when a consumer makes an online purchase, all the data is instantly accessible to different teams working together to fulfil the order:
‍

• Finance to record the purchase and payment method

• Marketing for order updates and email newsletters

• Fulfilment to process the order, locate products and pack it

• Logistics to arrange last-mile delivery and order tracking

• Customer support for details of all orders and interactions
‍

When data are collected from all these daily operations, they can be used for business intelligence and analytics to assist in decision making. Questions such as "which combination of products, payment methods and addresses are most prone to online fraud?" may help to flag suspicious orders and reduce business losses.

Collecting data is just the beginning

Collecting data is not enough to make your online business better. You need to have a data strategy in place to make the most of the data and turn them into real insights. A good way to start your big data journey is to choose a total experience platform like CINNOX that stores all your data and shares just the right amount of information.