4 Ways Big Data Can Improve The Customer Experience
Using Big Data to ensure a higher customer experience and ROI by leveraging information and technology. Using big data to understand better how customers feel. In this article, we discuss some of the ways in which data can be analyzed nowadays to improve the customer’s experience when shopping online. Some of these ideas have been discussed in the Blyp Question Hub.
In a highly digitalized world, the internet has become not a separate realm in which some small group of people invests a lot of their time but a space in which billions of us share ideas, pictures, and thoughts.
How can Big Data enhance the customer experience?
All of the data coming out of those who spend time on the web is being gathered by the systems that businesses currently use to process transactions, but it might be sitting there unproductively unless it is consciously exploited for the benefit of both customers and companies.
1. Creating tailored experiences
When shopping at a physical establishment, companies have the opportunity to make the experience quite remarkable for customers by managing different aspects of the environment such as the light, music, odor, and overall layout of the space in which the transaction occurs.
The experience has been conceived and designed in a way that prompts the consumer to buy whatever the store is offering just because he/she feels good about the place.
The idea of data analytics applied to online stores is that businesses can use all the data they have on a customer to make his/her experience as nice as possible to create a similar sense of comfort.
This can be achieved by creating tailored experiences. For example, the website could display colors, sounds, images, and other similar elements based on the user’s preferences. As a result, the overall shopping experience can be enhanced, and the odds of converting should increase.
2. More effective marketing
Digital advertising has become the most effective form of marketing nowadays due to the use of data points left by consumers every time they surf the web. By using this information, advertising platforms such as Facebook Ads and Google AdWords have created a huge database that can now be tapped to display ads to those who are more prompted to become buyers.
However, that might just be the entry point of a consumer from a marketing perspective as companies take over the process of nurturing and converting once a customer first visits a website or a certain landing page.
The combination of highly segmented audiences from digital advertising channels and the data collected by e-commerce systems like Shopify can be used in a way that increases the efficiency of the business’s marketing budget in the form of higher conversions.
3. Understanding trends and patterns better
Shopping trends can change rapidly and spotting these changes could be crucial to the performance of the business in the long run.
Think for example of a company that relies on two to three products to generate more than 80% of its sales. If consumers suddenly change their attitude toward the product, whether as a result of substitutes that are being introduced to the market or just because they were mostly a temporary fad, the online store will have to identify this attitude change rapidly to quickly modify its product line.
This would diminish the impact that such a change would have on its top-line performance and will prevent it from having to liquidate its inventory at a loss.
By using data such as customer’s feedback, sales figures, and other similar variables, a sophisticated software could conclude that a product’s demand is progressively fading and that can be insightful enough to prompt a store owner to change the entire value proposition of its business at a certain point in response to changes in consumer’s trends and patterns.
4. Improving performance across the board
With so much data flowing into e-commerce systems, it can be a bit overwhelming to start organizing and processing everything that is coming in to gain insights into the most crucial aspects of the business.
The introduction of software-as-a-service AI-powered data analytics tools specifically designed for the e-commerce industry, as is the case of Blyp, allows store owners to focus their time on what matters the most – building a great team, finding the best products, and sourcing from the best places.
In the meantime, big data can provide most of the much-needed insights that store owners can use to make timely decisions concerning their product lineup, marketing efforts, and front-end interface.
Big data will not necessarily replace managers in the long run. However, it should facilitate their lives by improving a business’s results rapidly through the analysis of the data that is coming into the store’s systems every day.
This can be achieved by data analytics software that generates valuable and actionable insights that end up improving a customer’s experience and the store’s overall performance at the same time.
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